{ "id": "AIBD-0216", "title": "Stanford's Tutor CoPilot (GPT-4 guidance for human tutors) raises K-12 math mastery 4 percentage points in a 900-tutor randomized trial with FEV Tutor", "summary": "RCT with 900 tutors and 1,800 grade 3–8 students in a southern US district: students whose tutors had Tutor CoPilot were 4 points more likely to master topics; 9 points for lower-rated tutors.", "date_observed": "2024-03-01", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "Wang, Ribeiro, Robinson, Loeb and Demszky of Stanford built Tutor CoPilot, a language-model system that gives human tutors expert-like suggestions during live sessions. They tested it with FEV Tutor, a virtual tutoring provider, and a large southern U.S. school district serving over 30,000 students. Nine schools took part. The district identified 1,787 students in grades 3–8, 80% Hispanic, who had performed below grade level. The preprint (arXiv, 3 October 2024) says that the study started at the end of March 2024 and lasted two months. The 900 tutors were evenly split between treatment and control. Students of treated tutors were 4 percentage points more likely to master topics. Students of lower-rated tutors gained 9 points, at about $20 per tutor per year. Education Week (31 October 2024), quoting co-author Susanna Loeb, reported that tutors using the tool were more likely to prompt students to explain. They were less likely to give away solutions. The 74 (7 October 2024) and MIT Technology Review (28 October 2024) reported that the system runs on OpenAI's GPT-4. They gave pass rates of 66% versus 62% on exit assessments and quoted outside researchers' caveats about the basic level of the mathematics. The preprint says that the study started at the end of March 2024.", "category": "general benefit", "unexpected": false, "purpose": "Tutor CoPilot was built to scale expert tutoring guidance to novice tutors in real time. Higher student mastery is that purpose.", "system": "Tutor CoPilot using GPT-4 and Bridge teaching strategies within FEV Tutor’s platform", "model_version": null, "developer": "Stanford University (Wang, Ribeiro, Robinson, Loeb, Demszky)", "deployer": "FEV Tutor with a large southern U.S. school district (nine schools)", "location": null, "domain": "Education", "segment": "K-12 virtual math tutoring (grades 3-8)", "benefit_type": "Improved Learning", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": null, "reason": "Students of tutors with the tool were 4 percentage points more likely to master topics, 9 points for lower-rated tutors (preprint abstract)." }, { "group": "organizational", "depth": null, "reason": "The tutoring provider's lower-rated tutors improved most at about $20 per tutor annually (preprint abstract)." } ], "ai_role": { "status": "assessed", "statement": "The model advised the human tutor and never taught the student directly. The measured change runs through tutor behavior (more prompting for explanations, fewer given-away solutions). Outside researchers quoted by MIT Technology Review note that the mathematics was relatively basic." }, "evidence": [ { "kind": "preprint", "citation": "Wang RE et al. Tutor CoPilot, arXiv:2410.03017v2 (study start and partner details).", "title": "Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise (v2 PDF)", "url": "https://arxiv.org/pdf/2410.03017v2", "date": "2025-01-26", "written_by": "makers", "quote": "We partnered with FEV Tutor (a virtual tutoring provider) and a large southern U.S. school district." }, { "kind": "other", "citation": "Rose E. Wang, Tutor_CoPilot_Demo.ipynb, commit 25c6eab7e416614f2033358bceddd30a4d5ca616, October 28, 2024.", "title": "Tutor CoPilot demonstration notebook", "url": "https://github.com/rosewang2008/tutor-copilot/blob/25c6eab7e416614f2033358bceddd30a4d5ca616/Tutor_CoPilot_Demo.ipynb", "date": "2024-10-28", "written_by": "makers", "quote": null }, { "kind": "news report", "citation": "Langreo L (31 Oct 2024). What Happens When an AI Assistant Helps the Tutor, Instead of the Student. Education Week (quotes Susanna Loeb, Stanford).", "title": "What Happens When an AI Assistant Helps the Tutor, Instead of the Student", "url": "https://www.edweek.org/technology/what-happens-when-an-ai-assistant-helps-the-tutor-instead-of-the-student/2024/10", "date": "2024-10-31", "written_by": "independent", "quote": "The tutors using Tutor CoPilot were more likely to prompt students to explain and ask guiding questions, and significantly less likely to give away solutions." }, { "kind": "news report", "citation": "Toppo G (7 Oct 2024). Study: AI-Assisted Tutoring Boosts Students' Math Skills. The 74 (quotes Rose E. Wang, Susanna Loeb, Amanda Bickerstaff, Benjamin Riley, Dan Meyer).", "title": "Study: AI-Assisted Tutoring Boosts Students' Math Skills", "url": "https://www.the74million.org/article/study-ai-assisted-tutoring-boosts-students-math-skills/", "date": "2024-10-07", "written_by": "independent", "quote": "The big dream is to be able to enhance humans." }, { "kind": "news report", "citation": "Williams R (28 Oct 2024). This AI system makes human tutors better at teaching children math. MIT Technology Review (quotes Rose Wang, Simon Frieder of Oxford, Mina Lee of Chicago).", "title": "This AI system makes human tutors better at teaching children math", "url": "https://www.technologyreview.com/2024/10/28/1106251/this-ai-system-makes-human-tutors-better-at-teaching-children-math/", "date": "2024-10-28", "written_by": "independent", "quote": "The tool isn't designed to actually teach the students math." } ], "replication": { "produced_by": [ "A language model prompted with a taxonomy of expert tutoring moves rather than answers", "Integration into a live virtual-tutoring platform where tutors can request suggestions mid-session", "Tutor-level randomization (900 tutors) with preregistered analysis" ], "must_hold": [ "Human tutors willing to use suggestions in real time", "Basic-level mathematics content (outside researchers' caveat)", "Students below grade level in under-served schools, the population studied" ], "echoes": [] }, "paired_incident": null, "headline": "Stanford's Tutor CoPilot lifts math mastery 4 percentage points", "metric": "students of treated tutors were 4 percentage points more likely to master topics", "comparator": { "against": "students of control-group tutors on the same platform who did not have access to Tutor CoPilot", "before": "62% student passing rate on exit tickets (control tutors)", "after": "66% passing rate (tutors with Tutor CoPilot), 4 percentage points higher", "basis": "measured", "quote": "Students working with treatment tutors were 4 percentage points (p.p.) more likely to pass their exit tickets (p< 0.01, 62% → 66% student passing rate from control to treatment).", "url": "https://arxiv.org/pdf/2410.03017v2" }, "later": { "status": "unknown", "date": null, "note": "The preprint was revised again on 10 October 2026, but no later deployment, replication or publication of the trial was found.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": "United States", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://arxiv.org/pdf/2410.03017v2", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://www.stanford.edu/about/; https://builtin.com/company/fev-tutor", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" }, { "date": "2026-10-22", "change": "Organization name standardized to Stanford University.", "source": null, "editor": "AIBD" }, { "date": "2026-10-25", "change": "Identified the AI model, software, configuration, and human controls from the original paper, supplement, or author documentation. Retained the reviewed paper first and the author’s notebook second, with the original publication preserved in version history.", "source": "https://arxiv.org/pdf/2410.03017v2", "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: three independent news reports, the makers' preprint and the makers' other. 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They tested it with FEV Tutor, a virtual tutoring provider, and a large southern U.S. school district serving over 30,000 students. Nine schools took part. The district identified 1,787 students in grades 3–8, 80% Hispanic, who had performed below grade level. The preprint (arXiv, 3 October 2024) says that the study started at the end of March 2024 and lasted two months. The 900 tutors were evenly split between treatment and control. Students of treated tutors were 4 percentage points more likely to master topics. Students of lower-rated tutors gained 9 points, at about $20 per tutor per year. Education Week (31 October 2024), quoting co-author Susanna Loeb, reported that tutors using the tool were more likely to prompt students to explain. They were less likely to give away solutions. The 74 (7 October 2024) and MIT Technology Review (28 October 2024) reported that the system runs on OpenAI's GPT-4. 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